In many situations, it is critical to rapidly estimate the safety of new or existing chemicals. For example, in the event of a sudden unexpected exposure of a chemical, such as with a chemical spill or a terrorist attack, an emergency response is needed to determine if and how to mitigate any potential risk from the chemicals' toxicity and to monitor this risk over time. To support chemical research and development, toxicity estimates are needed to ensure compounds are prioritized to minimize safety concerns. In these cases, it is not possible to generate traditional in vivo or even in vitro safety studies ue to the time needed to perform the experiments and interpret the data, as well as the cost associated with performing these tests. The only viable approach for generating this safety assessment is to use computational approaches that retrieve any existing historical data and, in the absence of data, calculate a prediction. These computational or in silico tools are becoming increasingly relied upon in product design and for product prioritization, yet they are not routinely used in regulatory decisions or emergency response situations. This situation is now changing through the introduction of a regulatory guideline that permits the use of in silico tools for prediction of bacterial mutagenicity of pharmaceutical impurities (the ICH M7 guidance). The development of an appropriate guideline along with supporting standard operating procedures (SOPs) has been instrumental in the adoption of in silico tools in this area. In this phase I proposal, two SOPs will be generated to support the evaluation of genetic toxicity and acute toxicity. They will outline how to 1) use and interpret available data, 2) generate predictions based on (Q)SAR methodologies and read-across approaches, how to appropriately interpret prediction results, 3) assess a confidence level for the results and 4) define the contents of an accompanying expert opinion. These SOPs will be created and then published in peer-reviewed publications by a working group of interested parties. Using the principles and procedures outlined in these SOPs, a single software application will be developed to rapidly identify data, generate toxicity predictions, assess prediction confidence and make recommendations on exposure thresholds. New in silico methods will be developed including (Q)SAR models to predict GHS (Globally Harmonized System of Classification and Labelling of Chemicals) classifications for acute toxicity as well methods for prediction of mutagenicity and clastogenicity. In phase II, several new SOPs will be generated to cover the use and interpretation of in silico approaches for all common toxic effects necessary for a complete safety assessment. Existing and newly developed models will be incorporated into to platform. This tool will be commercialized and licensed as an application to support the rapid response to safety questions, including emergency response situations and product design.